High temperature alters the growth reaction of Pottia protonemata.

Under gravistimulation, dark-grown protonemata of Pottia intermedia revealed negative gravitropism with a growth rate of approximately 28 μm·h⁻¹ at room temperature (20 °C). In 7 days, the protonema formed a bundle of vertically oriented filaments. At an elevated temperature (30 °C), bundles of vertically growing filaments were also formed. However, both filament growth rate and amplitude of the gravicurvature were reduced. Red light (RL) irradiation induced a positive phototropism of most apical protonemal cells at 20 °C. In a following period of darkness, approximately two-thirds of such cells began to grow upward again, recovering their negative gravitropism. RL irradiation at the elevated temperature caused a partial increase in the number of protonemal cells with negative phototropism, but the protonemata did not exhibit negative gravitropism after transfer to darkness. The negative gravitropic reaction was renewed only when protonemata were placed at 20 °C. A dramatic decrease in starch amount in protonemal apical cells, which are sensitive to both gravity and light, occurred at the higher temperature. Such a decrease may be one of the reasons for the inhibition of the protonemal gravireaction at the higher temperature. The observation has a bearing on the starch-statolith theory.     

Analysis and results of the 1995 Yuma ground penetration SARmeasurements

In July and October 1995, a large-scale airborne SAR experiment was conducted in the Yuma Proving Ground, Yuma, Arizona, to investigate ground penetration radar phenomenology and buried target detection. This paper describes the Yuma experiment and measurement results for many tactical, utility, and environmental targets deployed in the test     

Two-dimensional adaptive array for spatially separating andtracking uncorrelated sources

A new structure for the separation and tracking of uncorrelated sources through the use of a 2-dimensional adaptive array is proposed and investigated. The structure consists of a matrix preprocessing beamformer designed to result in outputs which are due to individual sources in the steady state. The preprocessing weights of the beamformer are calculated using the estimated locations of the sources and are updated periodically. Continuous estimation of the source locations is accomplished by using the beamformer outputs to adaptively eliminate correlated components in a reference element of the array while the structure proposed may have rather erratic initial convergence behavior, it has the advantages of being simple to be implemented, fast in tracking, and well suited for applications in mobile communication systems for increasing system capacity     

Analysis of an adaptive CFAR detector in non-Gaussian interference

Coherent signal detection in non-Gaussian interference is presently of interest in adaptive array applications. Conventional array detection algorithms inherently model the interference with a multivariate Gaussian random vector. However, non-Gaussian interference models are also under investigation for applications where the Gaussian assumption may not be appropriate. We analyze the performance of an adaptive array receiver for signal detection in interference modeled with a non-Gaussian distribution referred to as a spherically invariant random vector (SIRV). We first motivate this interference model with results from radar clutter measurements collected in the Mountain Top Program. Then we develop analytical expressions for the probability of false alarm and the probability of detection for the adaptive array receiver. Our analysis shows that the receiver has constant false alarm rate (CFAR) performance with respect to all the interference parameters. Some illustrative examples are included that compare the detection performance of this CFAR receiver with a receiver that has prior knowledge of the interference parameters     

Large-scale Coronal Heating, Clustering of Coronal Bright Points, and Concentration of Magnetic Flux

By combining quiet-region Fe XII coronal images from SOHO/EIT with magnetograms from NSO/Kitt Peak and from SOHO/MDI, we show that the population of network coronal bright points and the magnetic flux content of the network are both markedly greater under the bright half of the large-scale quiet corona than under the dim half. These results (1) support the view that the heating of the entire corona in quiet regions and coronal holes is driven by fine-scale magnetic activity (microflares, explosive events, spicules) seated low in the magnetic network, and (2) suggest that this large-scale modulation of the magnetic flux and coronal heating is a signature of giant convection cells. This revised version was published online in June 2006 with corrections to the Cover Date.